1/18/24 Marshall school panel Dr. Jonathan May is a Research Associate Professor at USC and Principal Scientist at the Information Sciences Institute (ISI), where he directs the Center for Useful Techniques Enhancing Language Applications Based on Natural And Meaningful Evidence. Dr. May's current research efforts include building empathetic chatbots to curb online toxicity, teaching agents to collaborate and compete in strategic gameplay, and developing interactive knowledge management systems. He was previously involved in multiple leadership positions in ISI’s efforts centered around translation and multilinguality. He has written and spoken about large language models extensively in the public sphere. May is an expert in architecture development for natural language processing, human-machine natural language interaction, computational journalism, machine translation, multilinguality, and transfer learning, with an extensive publication record that includes two outstanding paper awards and one best demo award. He has organized multiple NLP workshops and conferences at various service levels and currently is Treasurer of NAACL, the North American Chapter of the Association for Computational Linguistics. He is also an Amazon Scholar. 9/2023 AAAS Jonathan May is a Research Associate Professor of Computer Science at USC. May is an expert in natural language processing, human-machine natural language interaction, computational journalism, machine translation, multilinguality, and transfer learning. 7/2023 NSF APTO Dr. Jonathan May is a Research Associate Professor at USC and Research Team Leader at ISI, where he directs the Center for Useful Techniques Enhancing Language Applications Based on Natural And Meaningful Evidence. He is currently PI of ISI's efforts on DARPA Civil Sanctuary (building empathetic chatbots to curb online toxicity) and DARPA SHADE (teaching agents to collaborate and compete in strategic gameplay) as well as co-PI for ISI's efforts in DARPA’s KMASS and INCAS programs. He was previously involved in multiple leadership positions in ISI’s efforts centered around translation and multilinguality: PI of DARPA LORELEI, Co-PI of IARPA MATERIAL, and Co-PI of DARPA LwLL. He has written and spoken about large language models extensively in the public sphere. May is an expert in architecture development for natural language processing, human-machine natural language interaction, computational journalism, machine translation, multilinguality, and transfer learning, with an extensive publication record that includes two outstanding paper awards and one best demo award. He has organized multiple NLP workshops and conferences at various service levels and currently is Treasurer of NAACL. 1/2020 ASU Jonathan May is a Research Assistant Professor in the Computer Science Department at USC and the Information Sciences Institute (ISI). His research interests include automata theory, machine translation, semantic parsing, dialogue systems, information extraction, and creative generation. He received a PhD from USC in 2010 and BS/MS from UPenn in 2001. He was a co-organizer of the International Workshop on Semantic Evaluation (SemEval) and is the current treasurer of the North American Chapter of the Association for Computational Linguistics (NAACL). He has received a research award from ISI, an outstanding paper award from NAACL, and a best demo paper award from ACL. 11/2019 SemaFor Proposal Dr. Jonathan May is an Assistant Research Professor of Computer Science at USC and a Research Lead at the Information Sciences Institute (ISI). His research areas range from semantic parsing to machine learning to machine translation, spanning the statistical and neural eras and the commercial and academic domains. His research won outstanding paper and best demo paper awards at NAACL and ACL in 2018 for work on the formal properties of Recurrent Neural Networks and on universal tools for any-language NLP. Dr. May has four U.S. patents and is a PI and Co-PI on several large DARPA and IARPA programs, including DARPA-LORELEI and IARPA-MATERIAL. ??/2019 LwLL Proposal \textbf{Dr. Jonathan May} is a Research Assistant Professor at USC/ISI. His research in machine translation spans the statistical and neural eras and the commercial and academic domains. He is PI of ISI's contract in DARPA LORELEI, and co-PI of ISI's contract in IARPA MATERIAL. 2/2019 AIHacks Jonathan May is a Research Assistant Professor in the Computer Science Department at USC and the Information Sciences Institute. His research interests include automata theory, machine translation, semantic parsing, dialogue systems, and machine learning. He received a PhD from USC in 2010 and BS/MS from UPenn in 2001. His research won outstanding paper and best demo paper awards in 2018 for work on the formal properties of Recurrent Neural Networks and on universal tools for any-language NLP. 2/2019 Kairos Proposal Dr. Jonathan May is a Research Assistant Professor in the Computer Science Department of the Viterbi School of Engineering at the University of Southern California and a Research Scientist at USC/ISI. His research areas range from semantic parsing [Pus15] to transfer learning [Zop16] to machine translation [Her17]. He also has extensive effort in the design and application of unsupervised learning models [May07, Gra08] and efficient inference through networks [May10]. Prof. May's research won outstanding paper and best demo paper awards at NAACL and ACL in 2018 for work on the formal properties of Recurrent Neural Networks [Che18] and on universal tools for any-language NLP [Her18]. He is PI of USC/ISI's prime contract in DARPA-LORELEI and co-PI of USC/ISI's prime contract in IARPA-MATERIAL. Prof. May has extensive experience in shared task evaluations; apart from LORELEI and MATERIAL he has contributed to the ISI team's efforts in DARPA-BOLT and DARPA-GALE, has run two SemEval shared tasks on Abstract Meaning Representation parsing and generation [May16, May17], and developed cross-lingual NER methods in TIDES’ surprise language challenge [May03]. He currently serves as co-organizer of SemEval and treasurer of NAACL. 11/2016, JHU/Penn Invited Jonathan May is a Research Assistant Professor at the University of Southern California's Information Sciences Institute (USC/ISI). Previously, he was a research scientist at SDL Research (formerly Language Weaver) and a scientist at Raytheon BBN Technologies. He received a Ph.D. in Computer Science from the University of Southern California in 2010 and a BSE and MSE in Computer Science Engineering and Computer and Information Science, respectively, from the University of Pennsylvania in 2001. Jon's research interests include automata theory, natural language processing, machine translation, and machine learning. 9/2014: NAACL Board Jonathan May is a computer scientist at the University of Southern California Information Sciences Institute. Previously, he was a research scientist at SDL Language Weaver and a scientist at BBN Technologies. He received his Ph.D. in Computer Science from USC-ISI in 2010. Jonathan was Local Arrangements co-chair of NAACL HLT 2010 in Los Angeles and has been a member of the program committee for ACL, NAACL, and EMNLP since 2008. His research areas include machine translation, formal language theory, and semantics. 5/2014: ISI Jonathan May is delighted to return to ISI. Contrary to popular belief he has not been asked to re-do his PhD (obtained in 2010) due to "irregularities" but instead has joined the institute as a computer scientist, working on machine translation and semantics with Kevin Knight and Jerry Hobbs. Prior to this he was a research scientist at Language Weaver (now SDL). Before moving to Los Angeles Jonathan worked for BBN Technologies (now Raytheon), where he co-wrote his very first paper with current ISI director Prem Natarajan. Jonathan received bachelor's and master's degrees from the University of Pennsylvania. All readers of this biography are heartily encouraged to stop by office 940 for a complimentary sparkling water and lively discussion of translation, automata, semantics, telepathy, or other subjects.